How to use Batch Normalization with Keras?

The inputs to individual layers in a neural network can be normalized to speed up training. This process, called Batch...

Making more datasets available for Keras

Thanks to modern deep learning frameworks like Keras, it’s very easy to use particular datasets – which are included in...

Visualizing the structure of your neural network is quite useful for publications, such as papers and blogs. Today, various tools...

Flatten-T Swish is a new (2018) activation function that attempts to find the best of both worlds between traditional ReLU...

Datasets are crucial to functional machine learning models. Having a good dataset available can be the difference between success or...

In a different blog post, we studied the concept of a Variational Autoencoder (or VAE) in detail. The models, which...

Autoencoders are special types of neural networks which learn to convert inputs into lower-dimensional form, after which they convert it...

When you train a supervised machine learning model, you feed forward data, generating predictions on the fly. The comparison of...

Images can be noisy, and you likely want to have this noise removed. Traditional noise removal filters can be used...

Pure signals only exist in theory. That is, when you’re doing signal processing related activities, it’s very likely that you’ll...